Chi Square Tests

Mala Mahadevan discusses how to perform a Chi Square test:

For any dataset to lend itself to the Chi Square test it has to fit the following conditions  –

1 Both  variables are categorical (in this case – exposure to smoking – yes/no, and health condition – sick/not sick are both categorical).
2 Researchers used a random sample to collect data.
3 Researchers had an adequate sample size.Generally the sample size should be at least 100.
4 The number of respondents in each cell should be at least 5.

This is an easy case for using R over T-SQL—the Chi Square test is built in, whereas you have to roll your own T-SQL code.  Mala does show you how to do this from within SQL Server R Services as well.

Related Posts

Sentiment Analysis with Spark on Qubole

Jonathan Day, et al, have a tutorial on using Qubole to build a sentiment analysis model: This post covers the use of Qubole, Zeppelin, PySpark, and H2O PySparkling to develop a sentiment analysis model capable of providing real-time alerts on customer product reviews. In particular, this model allows users to monitor any natural language text […]

Read More

Running Spark MLlib to Feed Power BI

Brad Llewellyn shows how you can take Spark MLlib results and feed them into Power BI: MLlib is one of the primary extensions of Spark, along with Spark SQL, Spark Streaming and GraphX.  It is a machine learning framework built from the ground up to be massively scalable and operate within Spark.  This makes it […]

Read More

Categories

September 2016
MTWTFSS
« Aug Oct »
 1234
567891011
12131415161718
19202122232425
2627282930